{"id":"W2794488234","doi":"","title":"mirLibSpark: a scalable NGS microRNA prediction pipeline with data aggregation","year":2018,"lang":"en","type":"article","venue":"Research in Computational Molecular Biology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Scalability; Pipeline (software); microRNA; Computational biology; Data mining; Database; Biology; Gene; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001759742,0.00272817,0.001796635,0.002662972,0.001124532,0.002394106,0.00286862,0.001115691,0.01693017],"category_scores_gemma":[0.006552282,0.001629296,0.00209937,0.002801443,0.0004662803,0.00270199,0.003329362,0.001901783,0.01436811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007051307,"about_ca_system_score_gemma":0.0019956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006137147,"about_ca_topic_score_gemma":0.01137238,"domain_scores_codex":[0.9989115,0.0001298475,0.00009187862,0.0004454498,0.0003404748,0.00008085443],"domain_scores_gemma":[0.9981288,0.0007749558,0.0001121259,0.0005872278,0.0002613079,0.0001356566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002985802,0.0006057965,0.01244601,0.001976168,0.00166774,0.0008458332,0.0003510317,0.03498715,0.04697618,0.005833611,0.4809436,0.4103811],"study_design_scores_gemma":[0.0007324348,0.0002822473,0.0061646,0.0001147272,0.000395456,0.0004535486,0.0001495258,0.7849143,0.05464883,0.03582335,0.1160559,0.0002649523],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01732234,0.0009365634,0.3206151,0.0005783577,0.0003637322,0.0005136745,0.09223941,0.5627842,0.004646677],"genre_scores_gemma":[0.1200165,0.000583795,0.5625691,0.001032692,0.0002144668,0.001820718,0.2813969,0.02376015,0.008605718],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.01693017,"threshold_uncertainty_score":0.05663705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05219337998223342,"score_gpt":0.3800300473355545,"score_spread":0.3278366673533211,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}